Using linguistic analysis to understand how parents choose schools for their children

In economics, there is limited use of linguistic analysis to understand decision making processes and the contextual relationship between preferences. Over the last 6 months I have undertaken field research to understand how parents choose a school for their children and the decision architecture associated with this choice. The objective was not simply to collect information about stated preferences per se, but to understand the complexity of the decision process. I collected 22 exploratory interviews from Melbourne and regional Victorian parents – with a reasonable level of diversity in family demographics – looking at how they approach the problem of choosing a school for their children.

The purpose of these interviews was to principally explore for interesting economic ideas and questions arising from field observations. The intent was not to achieve a statistically robust collection of interviews of limited scope but instead to explore for opportunities that would warrant targeted econometric, experimental or theoretical research in the later part of my PhD. The presentation I gave at the 2014 ‘Cooperation and conflict in the family’ conference on an intergenerational discount heuristic is one of the ideas that arose from these field observations/interviews.

However, given that I had collected the interviews there was also the opportunity to investigate whether linguistic analysis can provide additional insights into how parents choose schools. The technique I have chosen to use is Latent Semantic Analysis (LSA) which I have been able to successfully program in python. LSA will allow the identification of linguistically revealed preferences from the way parents describe their decision processes in the interviews. These revealed preference words are closer to the personal context of the parent. In contrast, stated preferences given in surveys are more likely to be susceptible to social-desirability bias, framing effects and the limitations of defined preference lists.

In this way, linguistic analysis is particularly useful in designing discrete choice experiments where the wording of choices is strongly influenced by the nuances of context. I will be using this LSA analysis to construct preference attributes that are most likely to fit the consumption choices parents are making. The discrete choice experiment will then provide information on the monetary value of the trade-offs between choices/preference attributes. The core objective of the discrete choice experiment is to test whether different segments of the population make choice decisions based on signalling or specific wants, such as building their child’s self-esteem. My hypothesis is that parents sending their children to Public schools rely more strongly on signalling due to the higher uncertainty associated with the quality of the student cohort over time. While parents sending their children to Independent (private) schools avoid this ambiguity risk, focusing more strongly on specific consumption preferences (wants).

LSA is used to first calculate the semantic distance between individual interviews and target words processed as a pair. The latent semantic values of the individual interviews are then statistically analysed for clustering subject to school-type using the k-means method. The semantic distance between the centres of the resulting interview clusters and the target words is then calculated and graphed. The minimum number of clusters is selected subject to meeting the criteria of having a clustering p-value <0.01.

Target words can either indicate preferences such as ‘encourage’ or ‘choice type’ words such as ‘because’. For this analysis the word ‘encourage’ is the common word for all preference pairs. Pairing indicates the semantic ‘strength’ of a preference, the closer to zero the more salient the preference, and also provides insight into how the alternative word influences the semantic distance of the common word.

The table below is an example of some of the analysis. From these results it is interesting to note that in the first word pair ‘encourage’ and ‘support’, the interviews of parents sending their children to Independent (private) schools are grouped into two clusters that switch in the strength of their preference for schools ‘encouraging their children’ and ‘supporting their children’. This switch is common to all word pairs. The semantic strength of ‘community’ against ‘encourage’ is interesting because it suggests choice of school is strongly aligned with a sense of community for most of the groups and is strongest for parents sending their children to Catholic schools. At first glance, ‘reputation’ is counter-intuitively stronger for Public school parents than Independent (private) school parents. However, a school’s reputation is of greater concern to a parent sending their children to a Public school due to a higher level of ambiguity as to the quality of a school. Parents sending their children to Independent schools explicitly avoid ambiguity by the nature of their choice. Another interesting observation from the word-pairs is that academic results are more important for Catholic school parents and least important for Independent school parents. This suggests that parents sending their children to Independent schools are seeking outcomes beyond academic results. A number of parents in the interviews have indicated the importance of an Independence school in providing a more rounded education to develop the character of their child, for instance developing their confidence and self-esteem.